The subject matter discussed in this section should not be assumed to be prior art merely as a result of its mention in this section. Similarly, a problem mentioned in this section or associated with the subject matter provided as background should not be assumed to have been previously recognized in the prior art. The subject matter in this section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
Motion capture has numerous applications. For example, in filmmaking, digital models generated using motion capture can be used as the basis for the motion of computer-generated characters or objects. In sports, motion capture can be used by coaches to study an athlete's movements and guide the athlete toward improved body mechanics. In video games or virtual reality applications, motion capture can be used to allow a person to interact with a virtual environment in a natural way, e.g., by waving to a character, pointing at an object, or performing an action such as swinging a golf club or baseball bat.
The term “motion capture” refers generally to processes that capture movement of a subject in three-dimensional (3D) space and translate that movement into, for example, a digital model or other representation. Motion capture is typically used with complex subjects that have multiple separately articulating members whose spatial relationships change as the subject moves. For instance, if the subject is a walking person, not only does the whole body move across space, but the position of arms and legs relative to the person's core or trunk are constantly shifting. Motion capture systems are typically interested in modeling this articulation.
Most existing motion capture systems rely on markers or sensors worn by the subject while executing the motion and/or on the strategic placement of numerous cameras in the environment to capture images of the moving subject from different angles. Such systems tend to be expensive to construct. In addition, markers or sensors worn by the subject can be cumbersome and interfere with the subject's natural movement. Further, systems involving large numbers of cameras tend not to operate in real time, due to the volume of data that needs to be analyzed and correlated. Such considerations of cost, complexity and convenience have limited the deployment and use of motion capture technology.
Consequently, there is a need for improved techniques for capturing the motion of objects in real time without attaching sensors or markers thereto.